> For the complete documentation index, see [llms.txt](https://docs.aporia.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aporia.com/core-concepts/tracking-data-segments.md). # Tracking Data Segments Sometimes looking over our entire data doesn't supply us with enough insights to understand what is best to do. We need the ability to break our data into smaller pieces to reach valuable and sharp insights. This is exactly when data segmentation jumps to our help! Zooming into a specific data segment can help us understand if our overall performance degradation originates just in that segment or do we have a wide problem. Comparing two different segments can help us decide which one of them is more valuable to invest in our future campaign. ### Tracking Data Segments There are infinite ways to segment your data. Let us say we want to segment our subjects by their age. What interval between bins should we choose? should that interval be constant or maybe correlating to a real-world segmentation? Don't be tempted to create them all. Think about what segmentation choice can help you answer real valuable questions that may influence the actions you'll take. For example, gender is often just raw data and not a feature, but slicing your data by gender can help you surface performance differences or even biases. In such cases, you should consider even monitoring specific issues by segments. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.aporia.com/core-concepts/tracking-data-segments.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.